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Internship – Data Scientist / Data Engineer

Research, Assessment and Monitoring Division

WFP HQ Rome, Italy

The World Food Programme (WFP) is the leading humanitarian organization saving lives and changing lives, delivering food assistance in emergencies and working with communities to improve nutrition and build resilience. We are currently seeking to fill an intern position in the Research, Assessment and Monitoring Division (Climate and Earth Observation Unit), based at the WFP HQ in Rome.

BRIEF DESCRIPTION OF THE DIVISION:

The Climate and Earth Observation Unit (RAM-C), part of the Research Assessment and Monitoring (RAM) Division in WFP (World Food Programme) Headquarters, draws insights from satellite data streams to provide a range of crucial information products in support of WFP food security and aid operations.

The Unit’s diverse work ranges from monitoring of drought or extreme rainfall conditions to detection of changes in infrastructure assets, as well as high granularity assessments of natural hazard impacts, and mapping of cropland and crop types.

The Unit’s work draws on a wide variety of Earth Observation data from low resolution, long record, high frequency variables (rainfall, vegetation indices, land surface temperature) to very high (sub-meter) resolution data, as well as high-frequency, field scale resolution multi- spectral and SAR data from Sentinel-1 and Sentinel-2 platforms. Due to the often extremely large data volumes, these are processed at scale on the Team’s cloud-based computing infrastructure.

The Unit also promotes its analysis routines and tools to the community of analysts across WFP, both in other Units at Headquarters and in the field. To do so, the Unit is investing in enabling activities ranging from documentation, examples and capacity building efforts to maximize take-up of its tools across the organization.

Two data scientist / data engineer interns are sought to join the Data Science function in the Unit and contribute to the development of advanced analytical solutions to serve the above operations as well as contribute to their dissemination and promotion across the community of analysist across the organization.

GENERAL INFORMATION

• Title of Post: Internship
• Supervisor: Lead Data Scientist (1st level), Senior Climate and Earth Observation Advisor (Head of Unit) (2nd level)
• Unit: Climate and Earth Observation Unit
• Country: Italy
• Duty Station: Rome, HQ
• Duration of internship: 6 to 8 months
• Expected Start Date: April 11, 2023

DUTIES AND RESPONSIBILITIES

The intern will join the RAM-C Unit of the Research, Assessment and Monitoring Division at WFP HQ and work under the supervision of the Data Science Lead in coordination with the Data Engineering team.

The primary area of focus will be determined based on the successful candidate’s existing skillset and learning objectives and together with the candidate. It will also differ depending on whether this leans more towards data science or data engineering.

• Data Science: The intern will leverage statistical, geo-statistical and/or machine learning techniques to contribute to the analysis of complex climate, environmental and socio-economic data in support of the Unit’s products and services. These could involve, for example:
  • Advanced EO time series processing such as filtering, decomposition, lag-correlation analysis, and forecasting for the analysis of seasonal patterns across the globe.
  • Methodologies for multi-resolution data fusion (e.g. Landsat / MODIS) and the blending of ground-truth data with remote-sensed signals.
  • Analysis of dynamic land cover and quality patterns relevant for hazard mapping and environmental resource analysis using either classic or machine learning algorithms.
• Data Engineering: The intern will contribute to streamlining the use of the Unit’s stack for distributed scientific computing (dask-xarray-jupyter) among the community of analysts. This could involve, for example:
  • Reviewing and refactoring existing prototype code to be more scalable.
  • Consolidating internal and external knowledge of best practices around computation, data storage etc. into documentation, examples, benchmarking exercises, and tutorials.
  • Contribute to the production-readiness of parts of the Unit’s code base, by improving automation workflows, test coverage and documentation.
• The intern will also be accountable for:
  • Teamwork: The intern will be a committed and collaborative team member to support knowledge sharing and common practices within the Data Science function.
  • Communication: The intern will be responsible for quality code and documentation of their work and will present their results to stakeholders as needed.

QUALIFICATIONS AND EXPERIENCE

• Currently enrolled in an undergraduate or graduate programme from a recognized university OR recently graduated from an undergraduate or graduate programme (within six months prior to the application to the internship programme) from a recognized university;
• University course attendance in the past 12 months.

KNOWLEDGE & SKILLS:

Essential

• Demonstrated ability to apply statistical methods and/or data science and/or data engineering for the analysis of real-world problems.
• Ability and willingness to learn quickly, especially new tools, techniques, and software packages.
• Excellent Python programming skills, including some experience with data science and raster analysis libraries (eg. xarray, (geo-)pandas, numpy, scikit-learn, rasterio, etc.) and/or distributed computing frameworks (esp. Dask)
• Experience using Jupyter Notebooks

Preferred

• Experience in Earth Observation analysis. Demonstrated experience with remote sensing, agricultural, and/or large geospatial data.

• Experience using data engineering best practices (e.g. CI/CD, testing, git)
• Experience working with cloud platforms such as AWS, Azure, Google Cloud etc.

WORKING LANGUAGES

Excellent written and spoken English is required (proficiency/level C) with excellent technical reporting ability; good spoken and written French is an advantage.

SUPERVISION (Level/Methods of Supervision)

Under the direct supervision of the Lead Data Scientist for guidance and assessment of performance in specialized Data Science / Engineering domains and final supervision of the Head of Unit, Senior Climate and Earth Science Advisor for consistency of intern’s outputs with the Unit’s wider strategy and work plan.

TRAINING COMPONENTS

Throughout their assignment WFP interns have access to an industry leading learning platform, weLearn. Depending on opportunities and availability of funds, he/she may participate in WFP workshops or seminars, as appropriate.

Additionally, the Unit’s work provides a challenging but fertile ground for skill development and learning on state of the art methodologies for actual operational applications.

LEARNING ELEMENTS

At the end of the assignment, the Intern should:

• Gain full awareness of the relevance and applications of Climate and Earth Observation data for Humanitarian operations
• Expand knowledge of the applicability of machine learning and AI methods to use cases relevant for humanitarian agencies (hazard mapping, land cover change, climate tendencies)
• Be able to develop prototype near-operational workflows for climate and Earth Observation data, including automation, testing and documentation.
• Make significant contribution to some challenging issues in climate and Earth Obs data processing and analysis (real time filtering, super-resolution, data fusion)
• Gain experience in teamwork, including collaboration, maintenance and documentation of quality code, knowledge sharing and communication to stakeholders.

INFORMATION ON THE COUNTRY OF ASSIGNMENT – In person internship

• Living conditions in Rome, Italy

The security situation in Italy remains in line with other European Countries. There are no specific threats against the UN in Italy. Considering the ongoing defeat of Daesh in the war territories, the trend in the short and mid-term will most likely continue to see the return of the militants to the countries of origins, including Italy. Insurrectional anarchism remains sufficiently organized on the Italian territory, as it has been present for many years. This movement could target the UN in the context of its anti-capitalism/anti-western narrative. 2) Whilst UN staff continue to be victims of minor crime such as street robbery and apartment break-ins, the infrequency of attacks and random nature of locations do not indicate that UN staff are at an elevated risk in comparison to residents or tourists in Italy. 3) Italy’s national territory is exposed to a broader range of natural hazards than any other European country. The vulnerability of its population and built environment is often severe and has in some cases been exacerbated by human activities.

OTHER RELEVANT INFORMATION

• VA Reference no: 558958
• Closing Date: 20 March 2023 at 11:59pm Rome time

TERMS AND CONDITIONS:

• Interns receive a monthly stipend from WFP up to the maximum amount of US$1000 per month depending on the duty station of assignment.
• WFP is not responsible for living expenses, arrangements for accommodation, necessary visas and related costs.
• WFP will reimburse travel ticket for candidates who are nationals of developing countries and are pursuing their studies in their home country.
• WFP will recognize candidates’ educational credentials from recognised institutions that have been certified by competent international or national authorities such as the United Nations Educational, Scientific and Cultural Organization (UNESCO) or Ministries of Education.
• Candidates who bear any of the following relations to WFP staff members are not eligible to apply: sons, daughters, brothers or sisters.

WFP LEADERSHIP FRAMEWORK

These are the common standards of behaviour that guide HOW we work together to accomplish our mission.

Different expectations of behaviour are defined depending on your grade and role/responsibilities within WFP.

All employment decisions are made on the basis of organizational needs, job requirements, merit, and individual qualifications. WFP is committed to providing an inclusive work environment free of sexual exploitation and abuse, all forms of discrimination, any kind of harassment, sexual harassment, and abuse of authority. Therefore, all selected candidates will undergo rigorous reference and background checks. No appointment under any kind of contract will be offered to members of the UN Advisory Committee on Administrative and Budgetary Questions (ACABQ), International Civil Service Commission (ICSC), FAO Finance Committee, WFP External Auditor, WFP Audit Committee, Joint Inspection Unit (JIU) and other similar bodies within the United Nations system with oversight responsibilities over WFP, both during their service and within three years of ceasing that service.

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